Artificial Intelligence for the Indian Army: Challenges and Opportunities

8 min readApr 4, 2020

Enabling a smart force capable of fighting in both wartime and peacetime environments

Published as part of the Technologies for Non-Contact Warfare Series by
Ankit Tewari | Published: 02 April 2020, 06:34 AM IST

Introduction

When it comes to fighting wars, it is not merely the men but the deadly combination of well trained men and most capable machines that places a military in a superior and advantageous position. This fact becomes even more relevant when viewed from the perspective of Gen Bipin Rawat, Chief of Defence Staff (CDS) of the Indian Armed Forces who was speaking during an event on the theme of ‘Technologies for Non Contact Warfare’ at Manekshaw Centre in New Delhi. During the event held in late December, 2019, the General went on to say that “Non-contact warfare will help us in gaining advantage over the adversary in future. Therefore, it is important to understand the context in which we need to move forward in this direction”.

With the security situation in the India’s neighbourhood continuing to remain highly volatile, uncertain, complex and ambiguous and major military powers in the region investing in the development of sophisticated weapon systems and platforms for improving their operating efficiencies specifically in terms of combat capabilities, it becomes a need of the hour for the Indian armed forces in general and the Indian Army in particular to begin investing in modern technologies such as artificial intelligence to gain an advantageous position over the adversary. In fact, the situation at the present is so alarming that China alone outplays most of the other military powers in the Indian ocean region when it comes to fighting wars with intelligent machine with examples of smart airborne and underwater drones, smart surveillance grid etc.

While the developments in the past few years in the context of India have been positive with the launch of National Strategy on Artificial Intelligence by the elite government owned think tank NITI Aayog, the repercussions did not reach as expected in the context of adoption of artificial intelligence by the armed forces. Although, over the last couple of years many interesting exhibitions and events have provided the key industry and academic players to innovate for the needs of the Indian Army along with government bodies such as Defence Research and Development Organisation but most fo the efforts remained far from the combat deployment mainly due to lack of an organised body for considering such requirements, funding issues, regulating framework etc.

Global Military Artificial Intelligence Capabilities

United States, China and Israel have already been demonstrating a number AI projects for their defence forces at least since a decade with their armed forces launching system design challenges, coordinating with academia and industry for prototypes and even buying foreign platforms. Some notable and interesting projects, systems and technologies evolved and developed in this regard worth mentioning may include Project Maven which is jointly used by the US Air Force and CIA to comb through footage from uninhabited aerial vehicles and automatically identify hostile activity for targeting,

the Logistics Support Activity (LOGSA) being used by the US Army and developed in collaboration with IBM Watson for tailored maintenance schedules based on information pulled from the 17 sensors installed on each vehicle, the Autonomic Logistics Information System (ALIS) which is used to extract real-time sensor data and feeds the data into a predictive algorithm to inspect the aircraft or replace parts, the Multi-Domain Command and Control (MDC2) being used by the US Military for multi sensor data fusion in order to centralise planning and execution of air, space, cyberspace, sea, and land-based operations to achieve common operating picture,

the Multi-Utility Tactical Transport (MUTT) being used by US Army and US Marine Corps which acts as a platform to follow soldiers or vehicles around the battlefield to accomplish independent tasks, the Fire Weaver which is a Networked Sensor-to-Shooter System, developed by Rafael Advanced Defence Systems having algorithms to aid in targeting for commanders and soldiers, and the US Navy’s Anti-Submarine Warfare Continuous Trail Unmanned Vessel which can autonomously navigate the open seas, swap out modular payloads, and coordinate missions with other unmanned vessels all while providing continuous submarine-hunting coverage for months at a time.

Scope of AI for Indian Army

The Indian Army, while following its one of the finest traditions of continuing to evolve through the acquisition of modern intelligent platforms has been pushing extensively towards automation while having limited success too. In this regard, the creation of Army Design Bureau must be considered a notable achievement which presents the force with an organised framework to hold discussions with major industrial and academic players for the design and development of smart platforms. The scope of the design, development and deployment of artificial intelligence based systems for the Indian Army maybe simplified into the following four major areas-

Wartime operations: The operations of infantry, armoured and mechanised infantry forces may fall in this domain with applications such as detection of shooters in closely built up areas and real time recommendation for mission planning and execution in counterterrorism /counterinsurgency environments for infantry, realtime battlefield management systems for AI based battlefield transparency for armoured and, reducing sensor-to-shooter delays by target acquisition using computer vision and predictive maintenance of fleets for mechanised forces serve as some areas in which AI capabilities may be deployed;
Pseudo-Wartime operations: Most of the operations having relevance in both wartime as well as peacetime may fall in this domain such as information, surveillance and reconnaissance operations which may be classified as imagery intelligence applications for target identification, target classification, intent recognition, and decision support; signals intelligence applications which may utilise named entity recognition and intent recognition from call detail records, instant messaging or social media posts of extremist outfits to determine next sequence of actions; open source intelligence applications which may benefit from computer vision driven identification of enemy targets (both living and nonliving) using image/ video analytics of social media footage, and human intelligence applications for efficient optimisation of human intelligence assets, mission support etc;
Peacetime operations: All the operations which are carried out during peacetime while there are no actual wars may fall in this domain such as repair and maintenance operations having applications such as predictive maintenance for predicting next servicing, product life left and potential failures based on data from past years, supply chain and logistics applications for optimising routing, forecasting demand and supplies for efficient mission planning, force Protection applications for a regulated base access and securing perimeter using computer vision and speech recognition for enhanced base security, force structure maintenance applications for providing early warning to units and commanders about at-risk personnel (individuals at risk of committing suicides or indulging in violence with fellows based on the analytics of their behavioural, social and clinical data) are some of the examples.
Aid to civil authorities operations: These operations maybe simplified into the two major areas i.e. humanitarian assistance and disaster relief, and crowd and riot control. Both of the areas have a significant potential to be revolutionised with the arrival of a smart platform with applications such as automatic identification of individuals-at-risk during disasters by analysing social media chatter, pin-point-precision based support mechanisms or even monitoring of heavily crowded areas using computer vision methods to have a targeted response instead of a mass response for effective crowd management and riot prevention.

Recommendations

In the specific context of the Indian Army, the present moment appears as the golden hour to promote the design and development of intelligent combat systems based on artificial intelligence and therefore presents some brainstorming challenges which may eventually act as a series of recommendations for the force to implement. These are-

Accountability, Governance and Legal frameworks: The Indian Army in specific and the government in general needs to start formulating the regulatory procedures for such modern technologies as they leave a wide spectrum for misuse if not adequately addressed through a proper and well structured legal mechanism in order to ensure the accountability of such smart systems.
Lack of skilled manpower: India as a nation has arrived at the global centerstage of artificial intelligence with a delay where many developed nations already have established control. Therefore, the education and training being imparted to the Indian workforce is still not adequate to meet the challenges for innovating for such a huge defence industry.
Absence of training data: While having absence of formal data protection regulations, there is also a dearth of well established procedures to capture data for any future based analytics and it is slowly but steadily being streamlined with minimal impact already being felt in the other segments of governance such as revenue and taxation.
Interpretability and Transparency: While the rest of the world still struggles to understand the actual behaviour of most of the data centric algorithms as they continue to remain black boxes to a certain extent, we need to focus from the very beginning on such aspects to ensure proper usability and understand the context behind decisions made by such systems.
Privacy and security: Similar to the lack of regulations for data protection, there is a dearth of mechanisms to ensure the privacy and security of individuals as the non.contact warfare becomes a new norm.
Lack of coordination between academia, industry and government: Many good initiatives apart from the establishment of Army Design Bureau have already been undertaken with the Indian Institute of Technologies working closely with Defence R&D Organisation and the industry. Still a formal mechanism such as that of DARPA in united would surely bring more effectiveness.
Funding and Organisational Challenges: Finally, separate funding mechanisms must be developed to ensure that there are no budgetary hinderances in developing the state of the art systems apart from ensuring a dedicated body within the organisation to look in an specific way at the necessities of various arms and services.

Conclusion

The implementation of artificial intelligence capabilities for the Indian Army will present army as a futuristic and way more effective force and its impact may be realised in terms of an improved teeth-to-tail ratio which has been a major issue for the top brass since years. It will not only ensure the improved ability of the Indian Army to fight wars with better efficiency but will also result in least errors in combat with most of the time consuming decisions and processes being with handled by the machine under expert supervision of trained men.